Evidence map›Paper›PMID 34360820›Full record

ArticleInternational journal of molecular sciences2021

SLIDE-Novel Approach to Apocrine Sweat Sampling for Lipid Profiling in Healthy Individuals.

Aleš Kvasnička, David Friedecký, Alena Tichá, Radomír Hyšpler, Hana Janečková, Radana Brumarová, Lukáš Najdekr, Zdeněk Zadák

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Aleš KvasničkaFaculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic.ORCID 0000-0001-5973-316X
David FriedeckýFaculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic.ORCID 0000-0002-3448-9073
Alena TicháDepartment of Clinical Biochemistry and Diagnostics and Osteocenter, University Hospital Hradec Králové, Sokolská 581, 500 05 Hradec Králové, Czech Republic.ORCID 0000-0003-1329-1268
Radomír HyšplerDepartment of Clinical Biochemistry and Diagnostics and Osteocenter, University Hospital Hradec Králové, Sokolská 581, 500 05 Hradec Králové, Czech Republic.ORCID 0000-0003-0866-4883
Hana JanečkováLaboratory for Inherited Metabolic Disorders, Department of Clinical Chemistry, University Hospital Olomouc, 779 00 Olomouc, Czech Republic.ORCID 0000-0002-2581-6116
Radana BrumarováFaculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic.ORCID 0000-0003-1180-6977
Lukáš NajdekrFaculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic.ORCID 0000-0001-9559-5454
Zdeněk ZadákDepartment of Research and Development, University Hospital Hradec Králové, Sokolská 581, 500 05 Hradec Králové, Czech Republic.ORCID 0000-0002-7391-8619
Palacký University Olomouc · CZUniversity Hospital Hradec Králové · CZUniversity Hospital Olomouc · CZ

Funding

Agentura Pro Zdravotnický Výzkum České Republiky NU20-08-00367Ministerstvo Zdravotnictví Ceské Republiky FNHK, 00179906Ministerstvo Zdravotnictví Ceské Republiky FNOL, 00098892
6 · The paper itself

Abstract

We designed a concept of 3D-printed attachment with porous glass filter disks-SLIDE (Sweat sampLIng DevicE) for easy sampling of apocrine sweat. By applying advanced mass spectrometry coupled with the liquid chromatography technique, the complex lipid profiles were measured to evaluate the reproducibility and robustness of this novel approach. Moreover, our in-depth statistical evaluation of the data provided an insight into the potential use of apocrine sweat as a novel and diagnostically relevant biofluid for clinical analyses. Data transformation using probabilistic quotient normalization (PQN) significantly improved the analytical characteristics and overcame the 'sample dilution issue' of the sampling. The lipidomic content of apocrine sweat from healthy subjects was described in terms of identification and quantitation. A total of 240 lipids across 15 classes were identified. The lipid concentrations varied from 10

Indexed as

Specimen HandlingHealthy VolunteersHumansLipidomicsLipidsMetabolomicsSweatLipidsapocrine sweatlipidomicsmass spectrometrymicrosamplingprofiling

Identifiers

PMID34360820
PMCPMC8348598
OpenAlexW3186139365

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.